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--- |
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base_model: roneneldan/TinyStories-1Layer-21M |
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tags: |
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- generated_from_trainer |
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datasets: |
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- roneneldan/TinyStories |
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metrics: |
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- accuracy |
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model-index: |
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- name: tinystories_1layer_attn_mlp_C10k_k16 |
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results: |
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- task: |
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name: Causal Language Modeling |
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type: text-generation |
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dataset: |
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name: roneneldan/TinyStories |
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type: roneneldan/TinyStories |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.5091345939349958 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# tinystories_1layer_attn_mlp_C10k_k16 |
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This model is a fine-tuned version of [roneneldan/TinyStories-1Layer-21M](https://huggingface.co/roneneldan/TinyStories-1Layer-21M) on the roneneldan/TinyStories dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.1329 |
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- Accuracy: 0.5091 |
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- Multicode K: 1 |
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- Dead Code Fraction/layer0: 0.1880 |
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- Mse/layer0: 604.5097 |
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- Input Norm/layer0: 31.9987 |
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- Output Norm/layer0: 19.3897 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0005 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- gradient_accumulation_steps: 6 |
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- total_train_batch_size: 96 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: constant |
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- lr_scheduler_warmup_ratio: 0.05 |
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- training_steps: 10000 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Multicode K | Dead Code Fraction/layer0 | Mse/layer0 | Input Norm/layer0 | Output Norm/layer0 | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|:-----------:|:-------------------------:|:----------:|:-----------------:|:------------------:| |
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| 3.0494 | 0.05 | 500 | 2.9927 | 0.4177 | 1 | 0.0 | 805.1676 | 31.9986 | 10.3600 | |
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| 2.6986 | 0.1 | 1000 | 2.7080 | 0.4472 | 1 | 0.0084 | 739.3244 | 31.9985 | 12.7165 | |
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| 2.5145 | 0.15 | 1500 | 2.5252 | 0.4637 | 1 | 0.0546 | 697.1179 | 31.9984 | 14.4889 | |
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| 2.4197 | 0.2 | 2000 | 2.4093 | 0.4758 | 1 | 0.0988 | 670.0254 | 31.9983 | 15.7288 | |
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| 2.3541 | 0.25 | 2500 | 2.3404 | 0.4837 | 1 | 0.1337 | 651.1297 | 31.9983 | 16.6602 | |
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| 2.2742 | 0.3 | 3000 | 2.2907 | 0.4903 | 1 | 0.1499 | 642.6360 | 31.9983 | 17.3243 | |
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| 2.2488 | 0.35 | 3500 | 2.2565 | 0.4945 | 1 | 0.1575 | 640.3158 | 31.9983 | 17.7566 | |
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| 2.2287 | 0.4 | 4000 | 2.2333 | 0.4967 | 1 | 0.1613 | 638.8423 | 31.9983 | 18.0223 | |
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| 2.2576 | 0.45 | 4500 | 2.2155 | 0.4992 | 1 | 0.1676 | 639.7464 | 31.9983 | 18.1919 | |
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| 2.1901 | 1.02 | 5000 | 2.2026 | 0.5014 | 1 | 0.1696 | 638.1766 | 31.9984 | 18.3119 | |
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| 2.1686 | 1.07 | 5500 | 2.1935 | 0.5026 | 1 | 0.1716 | 638.6084 | 31.9984 | 18.4013 | |
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| 2.2158 | 1.12 | 6000 | 2.1833 | 0.5037 | 1 | 0.1779 | 632.9326 | 31.9985 | 18.5149 | |
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| 2.1843 | 1.17 | 6500 | 2.1760 | 0.5039 | 1 | 0.1797 | 631.2925 | 31.9985 | 18.5986 | |
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| 2.1339 | 1.22 | 7000 | 2.1696 | 0.5048 | 1 | 0.1819 | 627.9791 | 31.9985 | 18.7053 | |
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| 2.187 | 1.27 | 7500 | 2.1584 | 0.5063 | 1 | 0.1867 | 622.1227 | 31.9986 | 18.8338 | |
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| 2.1302 | 1.32 | 8000 | 2.1508 | 0.5071 | 1 | 0.1875 | 617.7162 | 31.9986 | 18.9493 | |
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| 2.1471 | 1.37 | 8500 | 2.1444 | 0.5082 | 1 | 0.1885 | 613.7248 | 31.9986 | 19.0666 | |
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| 2.1556 | 1.42 | 9000 | 2.1392 | 0.5087 | 1 | 0.1880 | 610.3757 | 31.9987 | 19.1817 | |
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| 2.1067 | 1.47 | 9500 | 2.1351 | 0.5091 | 1 | 0.1875 | 608.6866 | 31.9987 | 19.2836 | |
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| 2.1536 | 2.04 | 10000 | 2.1329 | 0.5091 | 1 | 0.1880 | 604.5097 | 31.9987 | 19.3897 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.17.0 |
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- Tokenizers 0.15.1 |
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